#  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at:
#
#       https://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
#  or implied. See the License for the specific language governing
#  permissions and limitations under the License.
import xgboost as xgb

from zenml import step


@step
def trainer(
    mat_train: xgb.DMatrix,
    max_depth: int = 1,
    eta: int = 1,
    objective: str = "binary:logistic",
    num_round: int = 2,
) -> xgb.Booster:
    """Trains a XGBoost model on the data."""
    params = {
        "max_depth": max_depth,
        "eta": eta,
        "objective": objective,
    }
    return xgb.train(params, mat_train, num_round)
